Traditional sensory evaluation of food is affected by subjectivity and other factors, resulting in significant limitations. Electroencephalography (EEG), owing to its advantages of high temporal resolution, non-invasiveness, and real-time dynamic monitoring, offers an objective neurophysiological perspective and analytical approach to address this issue, effectively advancing food science research from subjective descriptions to objective neural decoding. This paper systematically reviews the applications of EEG in food flavor recognition and prediction, objective evaluation of food quality, and analysis of food nutrition and consumer behavior. In light of the current state of technological development, it is proposed that multimodal technology integration and machine learning empowerment can be leveraged to optimize the application of EEG in the food domain, aiming to provide a systematic theoretical reference for further in-depth application research of EEG in the food field.