A biased sample occurs when the group selected for a statistical study or survey is not random and doesn't properly represent the larger population. This is a result of sampling bias sampling bias which occurs when the sample of the population is not representative of the population at large.
An example of a biased sample could be seen in a person taking a poll of how many people enjoy eating shrimp. The person asks 100 people how they feel about shrimp and 90 people said they enjoyed it. "Wow! 90% of people enjoy shrimp!" thinks the pollster. But they soon realize they have a biased sample- they stationed themselves on a boardwalk outside of many popular seafood restaurants. There were many people walking in that area that liked shrimp because they were headed to and from seafood restaurants. If the pollster had stationed themselves in front of the post office or DMV (somewhere that wouldn't be influenced by particular food tastes) they would have gotten a more accurate representation of the larger population's feelings about shrimp.