The same effect can be observed if you've ever been a software developer where you're told what solution to build without any of the context of the problem you're solving. "We need an FTP server, quick, ops, get on that." leading into "Oh, it turns out the customer didn't need that to receive our emails" leading to a bunch of very puzzled devops.
I would say it is definitely a form of context, but when people think of LLM context windows in terms of coding is more technical context related: "what has been done before, what's the coding task at hand." etc.
However, I think that there is a philosophical portion to that context as well: "What problem is this feature supposed to help with? How would you verify that passing unit tests means that the code is working as intended? Does this feature need to exist at all?" LLMs usually need these to be provided to them explicitly since they are not good at inferring the correct intent compared to humans, otherwise they just make something that looks right but doesn't work right.
Yeah lol. That definitely does not sound like philosophy. Giving a "why" you want to implement a feature and make particular changes will help the AI stay on track much better than if it is driving blind. It can't make choices without understanding what the desired outcome is.