It is not entirely clear to me what are you looking for and why.
If you want the best performance you are almost surely bound to use compiled language such as Fortran[1], C++ or C. Of course, you can always use almost any "higher level language" such as Python, Ruby or whatnot to glue together routines from libraries written in some "low level language" as C, Fortran, etc. Octave, Matlab and Sage come to mind. NumPy is quite good example of this approach, since almost all of its core functions are written in C (i.e. LAPACK).
If, on the other hand, you want to experiment with algorithms themselves, you can implement them in Haskell or (oca)ML or some other "mathematicians friendly" language. Also, succinct syntax and lack of side effects means it's much easier to prove correctness. Moreover there are area specific systems/languages as LiE, Macaulay2, Singular, GAP, ...
Writing basic routines (such as those from Numerical Recipes) in any other language than C, C++ or Fortran means that
- you are doing an exercise
- you are trying to solve a problem in a language where you can't use functions from libraries written in C/C++/Fortran
- you need numerical routines in a big (i.e. not feasible to rewrite in C/C++/Fortran) project where calling an external library causes unwanted overhead (this can be the case for example with Java).
[1] Please note that modern Fortran is quite high level language with functional and object-oriented features.