In an important sense, it only becomes a finite algorithm. It isn't one. You cannot write the finite sequence of instructions down. It's got loops.
To your point about approximations vs not, if you have an algorithm that, for any desired approximation accuracy can compute the square root to that accuracy in a finite number of steps, then that process is as much "the square root" as anything involving the real numbers.
Not really, since approximations, no matter how accurate, don't preserve algebraic properties. You only get to know what it's bigger/smaller than.
If you are representing or thinking of "sqrt(2)" as "the positive solution to x^2 = 2", then you preserve algebraic properties. But you generally (correct me if I'm wrong) don't get to know whether it's bigger or smaller than something else of the form "the _choose_uniquely_ solution to _some_equation_" unless you rely on an argument where you invoke approximations.
> In mathematics and computer science, an algorithm (/ˈælɡərɪðəm/ (About this soundlisten)) is a finite sequence of well-defined, computer-implementable instructions, typically to solve a class of problems or to perform a computation.
Newton's method is finite too. You perform finitely many iterations. It doesn't calculate roots. It calculates their approximations.
[1]: <https://en.wikipedia.org/wiki/Algorithm>