It is good to at least understand how recursion works, because some algorithms are naturally recursive and thus much easier to express using recursion.
Also, recursive algorithms (or implementations) are not inherently slower than iterative ones. In fact, every recursive algorithm can be implemented by an equivalent iterative implementation at the cost of having to keep track some intermediate/temporary values yourself, where the recursive version automatically keeps track of those in the function call stack.
One example of a naturally recursive algorithm is if you want to apply an operation to all the nodes of a tree. The most natural implementation here is to have a function that performs the operation on one node and calls itself recursively for each of the children of the node.
For some algorithms, like calculating a Fibonacci sequence, recursion seems natural, but a naive implementation will be much slower than an iterative implementation, because the recursive version keeps re-doing the same work over and over again. This just means that for those particular algorithms, recursion may not be the best choice, or that you need to use some techniques to remember intermediate values that might be needed again elsewhere in the algorithm.
For other algorithms, in particular those that use divide-and-conquer tactics, you will find that you need a stack to keep track of some thing in the iterative solution. In those cases, a recursive version is much cleaner, because the stack handling becomes implicit.