Short answer: No, there is not. at least not that I know of. There is nothing provided with MATLAB, nor have I even provided that option as part of my SLM toolbox.
Longer answer: There are many reasons why this will be difficult. A big one is "distance" implies the orthogonal distance to the curve, which becomes a moderately difficult problem to solve.
Even if you intend distance to be strictly in y, maximum distance to a list of points will take some effort to write. Were I to write code to solve this, I would probably set it up as a constrained smoothing spline of sorts. So adjust the regularizer weight so that the maximum residual becomes no larger than the given tolerance. Thus you can write a smoothing spline as the solution to a problem
arg min {lambda*(norm(y - yhat)) + (1-lambda)*int(yhat'' ^2)}
So two terms. One is the norm of the residuals. The second term is the integral of the square of the second derivative. When lambda==1, we have an interpolating spline as the result. When lambda=0, all weight goes into making the spline as smooth as possible, so you get a straight line. You could choose lambda such that the result is as smooth as possible, such that the maximum residual does not exceed the target. The code would involve a simple univariate optimization on lambda.
(The above scheme would get nasty if you tried to use orthogonal distance to a spline.)
More to the point as to why it does not exist is nobody seems to want such a tool, at least I've never seen it requested.
So, no there is no tool to do what you want, but feel free to write it. If you do a good job, then post it on the File Exchange.
