Discrimination-aware learning is an approach in machine learning that seeks to ensure models do not perpetuate or exacerbate bias and discrimination present in training data. It involves techniques to detect, mitigate, and evaluate bias, ensuring fairness and equity in algorithmic decision-making processes.