Machine Learning (ML) and Deep Learning (DL) are playing an increasingly critical role in enhancing security and privacy within the Internet of Medical Things (IoMT). As IoMT environments face diverse threats and complex attack vectors, understanding their unique security requirements is essential. This paper explores the key challenges related to IoMT security, presents various ML and DL methods applied in this context, and reviews existing security solutions. It also identifies open research problems that must be addressed to strengthen the resilience of IoMT systems.