Equivalence Partitioning is best defined as:

Equivalence Partitioning is best defined as an analysis technique that divides inputs into groups that are expected to exhibit similar behaviors. This approach simplifies the testing process by identifying different classes of input values that can be treated the same way. The underlying principle is that if one value from a partition is tested, the others will likely yield the same result, thus reducing the number of test cases while still ensuring adequate coverage for various input scenarios.

By creating partitions based on expected behavior, this technique allows testers to focus their efforts on representative values rather than exhaustively testing every possible input. It not only enhances efficiency but also improves the overall effectiveness of testing by systematically covering the different possibilities that could occur within a given input domain.

Other options provided do not accurately reflect the essence of Equivalence Partitioning. For instance, limiting its application strictly to time-related data classes neglects the broader applicability across various types of input data. Additionally, it is not a form of white-box testing, which focuses on code structure and internal logic rather than input behavior. Lastly, portraying it as a method to reduce test coverage is misleading; rather, it is designed to optimize test coverage efficiently by categorizing inputs.