A Non-Deterministic Turing Machine (NDTM) is a theoretical model of computation that extends the concept of a standard Turing machine. Unlike a deterministic Turing machine, which has a single possible action for each state and input symbol, an NDTM can have multiple possible actions. This means that for a given state and input, the machine can "choose" from several transitions, allowing it to explore many computational paths simultaneously. NDTMs are primarily used in the field of computer science to study the complexity of problems. They are particularly important in the context of complexity theory and NP-completeness, where they help define classes of problems that can be solved efficiently. While NDTMs are not physically realizable, they provide valuable insights into the limits of computation and the nature of algorithmic problem-solving.