Data annotation in machine learning serves the purpose of labeling or tagging data to help machines understand and learn from it. This process is crucial in training algorithms, as annotated data provides the ground truth for supervised learning. For example, images may be labeled with identifying objects, while text could be tagged for sentiment. High-quality data annotation improves the accuracy and performance of machine learning models, facilitating their ability to make informed predictions or decisions based on the input data they process.