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Non-deterministic polynomial time (NP) is actually a marker used to point to a set of problems and bounds of the capability of certain types of computing. NP refers to the set of problems that can be solved in polynomial time by a non-deterministic Turing machine.
Non-deterministic polynomial time is based on the phrase "polynomial time," which refers to whether an algorithm can perform within certain bounds relevant to speed. Polynomial time emerged as a way to talk about feasibility of algorithm work and development.
If a problem is in non-deterministic polynomial time, the non-deterministic Turing machine can first guess at the solution, and then run a verifiable algorithm that will confirm whether or not that guess was correct. Verifier-based definition or machine definition programs will in essence test the initial choices of the non-deterministic Turing machine to verify results.
All of this is highly theoretical computing structure. While machine learning has been making inroads in going beyond deterministic systems, the idea of verifying non-deterministic choices is still in its infancy. Look for more development on this frontier of computing.