Bias mitigation techniques are strategies used to reduce or eliminate biases in data and algorithms, ensuring fair and ethical decision-making processes in machine learning models. These techniques are essential for promoting inclusivity and accuracy, helping to prevent discrimination and improve model reliability across diverse populations.