Data annotation is the process of labeling or tagging raw data, such as images, text, or audio, to make it understandable for machine learning models. This process adds metadata that provides context, which is crucial for training algorithms in a process called supervised learning. By providing labeled examples, data annotation enables AI models to identify patterns, make predictions, and perform tasks like object recognition, speech-to-text, and text analysis.