NP COMPLETE MEANS THE PROBLEMS IN COMPUTER SCIECNCE FIELDS MAINLY THE ALGORITHMS RUN FOR POLYNOMIAL RUNTIME, Problems in the class P can be solved quickly by computers, while problems in NP can be quickly verified if given a solution. NP-complete problems are the toughest ones within NP; if you can solve one NP-complete problem quickly, you can solve all NP problems quickly. This concept is significant because it helps us understand the limits of algorithmic efficiency, guides us in designing better algorithms (often leading to approximate or heuristic methods), and relates to the profound P vs. NP question, which asks if every problem whose solution can be verified quickly can also be solved quickly. An example of an NP-complete problem is the Boolean satisfiability problem (SAT), which involves finding an assignment of truth values to variables that makes a Boolean formula true. NP-completeness helps classify and approach solving complex problems across various fields.