Have you ever met someone and had an instant connection? They vote for the same political party and they like pizza and they like Harry Potter?! They were obviously your soulmate. But then, a couple weeks later you start to realize that you have differing religious beliefs and they prefer a different kind of soda. Alas, you are not truly soulmates.
That is an instance of the Texas Sharpshooter Fallacy. It is when you pay particular attention to a small set of data, and ignore the larger data. In this case, it is ignoring the fact that the vast majority of people vote for one of two political parties, so the there is a significant chance they vote for the same one you do. A lot of people like Harry Potter and pizza. If you look at those details in the instance of two people, they appear significant. But once you zoom out and look at a broader scale, those details do not mean very much.
Humans want there to be meaning. We want to believe that things happen for a reason. No matter your spiritual or philosophical beliefs, certain things are statistically likely.
The Texas Sharpshooter Fallacy is about acknowledging what situations are statically likely to occur.
Slate has a really interesting article (http://www.slate.com/articles/health_and_science/medical_examiner/2013/03/cancer_cluster_in_toms_river_new_jersey_the_link_to_a_superfund_site_is.single.html) about a few communities in which people were searching for reasons as to why people were developing cancer. They wanted an explanation, so they looked for environmental causes. A percentage of the population gets cancer, no matter where they live. Certain things are statistically more likely to happen. Certain factors make them more likely, but not everything happens for a reason, besides the fact that things happen every so often.
This fallacy is also about ignoring certain parts of data, whether it is done subconsciously or not, in order to reach the conclusion that we want. In that way it is related to confirmation bias, in that we tend to only focus on information that supports our line of reasoning.
I find this fallacy interesting because it one that I have definitely used before. I am excited that now that I now about this fallacy, I can avoid using it and think about if the conclusion I have reached would be true if I looked at data that examined things broadly.