Interactive machine learning is a research field and methodological approach investigating systems where a human user actively participates in or guides the machine learning process. This typically involves iterative interaction, such as providing feedback, labeling data, or steering exploration, to enhance model performance, efficiency, interpretability, or alignment with specific human objectives, especially in complex or data-limited domains.