Data labeling is a crucial process in machine learning and artificial intelligence, where raw data is annotated with meaningful tags or labels. This enables algorithms to understand and interpret the data effectively. For instance, in computer vision, images may be labeled to identify objects, while in natural language processing, text can be tagged for sentiment analysis. The quality of labeled data directly impacts the performance of machine learning models, making accurate and efficient labeling essential. Various tools and techniques are available to streamline this process, ensuring that datasets are ready for training and analysis.