Computational complexity is a field in computer science that studies how the resources needed to solve a problem, like time and memory, grow as the size of the problem increases. It helps us understand which problems can be solved efficiently and which ones are too difficult to tackle in a reasonable amount of time. One key concept in computational complexity is the classification of problems into categories such as P (problems solvable in polynomial time) and NP (problems for which a solution can be verified quickly). This classification helps researchers identify the limits of what computers can do and guides the development of algorithms.