Feature engineering is the process of selecting, transforming, and creating new features (variables) from raw data to improve the performance of machine learning models. It plays a crucial role in the success of many machine learning projects because the quality and relevance of the features used can significantly impact the model's ability to make accurate predictions or classifications.