Data labeling is the process of annotating data with meaningful tags to make it understandable and usable for machine learning models, ensuring that algorithms learn from accurately categorized information. It is a critical step in supervised learning, as the quality of labeled data directly impacts the effectiveness and accuracy of the model's predictions.