Algorithmic bias refers to the systematic and unfair discrimination that can occur in computer algorithms. These biases often arise from the data used to train algorithms, which may reflect existing prejudices or inequalities in society. As a result, algorithms can produce outcomes that disadvantage certain groups based on characteristics like race, gender, or socioeconomic status. This issue is particularly concerning in areas such as artificial intelligence, machine learning, and data analysis, where biased algorithms can influence decisions in hiring, lending, and law enforcement. Addressing algorithmic bias is essential to ensure fairness and equity in technology-driven processes.