What is the Woodbury inverse parameter in GPy?

Question

I got a piece of code from someone, who trained a GPRegression model from GPy:

import numpy as np
import GPy

x = np.linspace(0, 1, 10).reshape(-1, 1)
y = np.sin(x)

model = GPy.models.GPRegression(x, y, GPy.kern.RBF(input_dim=1))

print(model.posterior.woodbury_inv)

At the end they print the model.posterior.woodbury_inv.

I have difficulties understanding what exactly that is. According to the description of that parameter in the GPy documentation it's the "inverse of the Woodbury matrix". The term "Woodbury matrix" was new to me prior, but from what found on Google it's a formula to calculate the inverse of a the matrices (A+UCV). I don't quite understand if the GPy description and what I found while searching referes to the same thing.

Can someone please explain to me what the Woodbury matrix is and, if possible, what exactly the "model.posterior.woodbury_inv" parameter is?