Fairness in machine learning addresses the need to ensure that algorithms do not perpetuate or amplify biases, leading to equitable outcomes across different demographic groups. It involves identifying, measuring, and mitigating biases in data and models to prevent discrimination and promote inclusivity in automated decision-making processes.