The Kolmogorov complexity of a binary string can be defined in terms of a prefix-free binary encoding of Turing machines that operate on a binary tape. Then if $x$ is a binary string, $K(x)$ is the length of the shortest encoding of any Turing machine that halts with $x$ on the tape when given an initially empty tape.
It's possible to use the same setup to describe the shortest Turing machine encoding corresponding to a computable function. We need one extra parameter it seems: a binary prefix-free encoding of the natural numbers. Given that, it's possible to define the length of the shortest Turing machine encoding corresponding to any particular computable function $\mathbb{N} \rightarrow \{0,1\}^*$ (or by decoding with the same function, $\mathbb{N} \rightarrow \mathbb{N}$). Or with the convention that membership is equivalent to an empty output tape, we can talk about the length of the shortest Turing machine encoding corresponding to a computable set of natural numbers (or the bits of a computable real). It doesn't really matter what natural number encoding we choose, as long as it is computable, since the result is still defined up to an additive constant.
Can I just call this the Kolmogorov complexity of a function, or of a set, or of a real, and be understood?