Algorithmic fairness is a research field and methodological approach dedicated to identifying, analyzing, and mitigating bias and discrimination in the design, development, and deployment of algorithmic systems. It investigates how algorithms can produce disparate impacts on different demographic groups, develops formal definitions and metrics for various conceptualizations of fairness, and explores technical and socio-technical strategies to enhance equity and accountability in automated decision-making processes. Its significance lies in ensuring ethical outcomes and preventing harm in the increasing application of algorithms across critical societal domains.