Somehow I got into an efficiency/performance focused mindset pretty early on, so I appreciated the algorithm analysis when I got to it (though I thought then and still do think that big O notation simplifies it a bit too much... Those dropped terms can be just as or even more significant as the final term when it comes to typical data sets, but it's still useful in understanding how an algorithm scales).
And I'd say that just going over the existing data structures and understanding their strengths and weaknesses can help just by being aware something exists. Like if all you know are arrays and linked lists, you'll probably struggle a bit to handle key/value pairs. And then, once you learn about them, you might use them for everything and then wonder why your code runs so slowly.
And the main reason why I'd like more people to be aware of how to be good programmers is that there seems to be a lot of people that just go from "something I'm doing as a hobby" to "something I'm doing for money" or "a large hobby project that has been picked up by the community". And software quality has been dropping at a similar rate to how much hardware is improving.
But you're right that, without the greater context, a lot of it can be confusing and can beg the question of "why do I need this?"