It's an old AI term meaning roughly "find a solution that isn't (likely) optimal, but good enough for some purpose, without too much effort". It implies that either your computer is too slow for it to be economical to find the true optimum under your models, or that you're too dumb to come up with the right models, thus the popularity of the idea in AI research.

You can be impressed if someone starts with a criteria for what "good enough" means, and then comes up with a method they can prove meets the criteria. Otherwise it's spin.