In the context of machine learning, "data synthesis" refers to the process of creating new, synthetic data samples from existing datasets. This technique is employed to expand datasets, particularly when there is limited data for certain classes or scenarios. Data synthesis can improve the robustness of machine learning models, enhance training capabilities, and mitigate issues related to overfitting or data imbalance.