Algorithmic bias refers to the systematic and repeatable errors in a computer system that create unfair outcomes, often privileging one arbitrary group of users over others. It arises from various sources, including biased training data, flawed assumptions in model design, and lack of diversity in development teams, leading to significant ethical and social implications in AI deployment.