Machine bias is the effect of an incorrect assumption in a machine learning (ML) model that's caused by overestimating or underestimating the importance of a particular parameter or hyperparameter.
Bias can creep into ML algorithms in several ways. AI systems learn to make decisions based on training data, which can include biased human decisions or reflect historical or social inequities, even if sensitive variables such as gender, race, or sexual orientation are removed.
Source: techopedia.com