Data annotation is the process of labeling or tagging data with relevant and accurate information to make it useful for machine learning algorithms. This process involves assigning categories or tags to data points, such as images, text, or audio, based on specific criteria or parameters. Data annotation is essential for training and improving the accuracy of machine learning models by providing labeled datasets for training and testing. It helps algorithms identify patterns and make predictions based on the annotated data. Data annotation can be done manually by human annotators or automatically using software tools.