The Gram-Schmidt Process is a mathematical technique used to orthogonalize a set of vectors in an inner product space. This means it transforms a linearly independent set of vectors into an orthogonal set, where each vector is perpendicular to the others. This process is particularly useful in simplifying problems in linear algebra and is often applied in areas like computer graphics and signal processing. The procedure involves taking a vector and subtracting its projections onto the previously orthogonalized vectors. This ensures that each new vector added to the set is orthogonal to all the others. The result is a new set of vectors that can be used to form an orthonormal basis for the vector space.