The training set used to train the ML model can be labeled by humans who may have been biased during the tagging process. For example, in a system that predicts the success rate of a job candidate, if the labeling was done by a person who is biased (intentionally or unintentionally), the ML model will learn the bias that exists in the labeled data set it receives.