What matters is that the equation accurately predict Y from X within the range of your data. This approach can be useful in some situations. Don't use it when the goal of curve fitting is to fit the data to a model based on chemical, physical, or biological principles. Don't use a computer program to avoid making a scientific decision. The term is often used to refer not to nonlinear regression, but rather to polynomial regression.
Programmers prefer polynomial regression, because it is so much easier to program.
That's why it is built in to so many spreadsheet and graphics programs. But few biological or chemical models are described by polynomial equations, so polynomial regression is of limited usefulness to scientists. Cubic spline is not a data analysis method Cubic spline curves are smooth curves that go through every data point. In some cases, a cubic spline curve can look attractive on a graph and work well as a standard curve for interpolation. A line is described by a simple equation that calculates Y from X, slope and intercept.