Abstract: In recent years, machine learning (ML) methods have emerged as crucial tools in inertial confinement fusion (ICF) research. This paper compiles ML algorithms employed in ICF studies over the past decade, elucidates their operational principles, distinctive features, and application scenarios, provides representative implementation cases, and analyzes developmental trends within this interdisciplinary domain.